Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners. In the present work, based on an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, we propose a hybrid optimization method for the structural design optimization of beam-plate structures, which covers three optimization levels: dimension optimization, topology optimization and section optimization. The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints. The kernel optimization procedure (KOP) uses BESO to obtain the optimal topology from a ground structure. To deal with beam-plate structures, the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure. In the first optimization level, a series of ground structures are generated based on different dimensional parameter combinations, the KOP is performed to all the ground structures, the response surface model of optimal objective values and dimension parameters is created, and then the optimal dimension parameters can be obtained. In the second optimization level, the optimal topology is obtained by using the KOP according to the optimal dimension parameters. In the third optimization level, response surface method (RSM) is used to determine the section parameters. The proposed method is applied to a hatch cover structure design. The locations and shapes of all the structural members are determined from an oversized ground structure. The results show that the proposed method leads to a greater weight saving, compared with the original design and genetic algorithm (GA) based optimization results.     

双侧壁导坑与 CD 法对超大断面隧道开挖影响分析

随着高等级公路的大量建设,超大断面隧道不断涌现。目前对超大断面隧道力学性质与支护结构机理及其施工方法的研究仍然不足。以郑州市中原路西延线韩门超大断面隧道为工程依托,采用有限元分析方法,对超大断面隧道开挖过程进行有限元模拟,揭示双侧壁导坑法与CD法开挖方式下隧道围岩的变形规律、应力分布特征等,为超大断面隧道设计和施工提供理论依据,并通过现场监测予以验证。揭示大断面隧道开挖变形机理,优化施工技术,以指导超大断面隧道设计和施工。     

Optimal linear phase finite impulse response band pass filter design using craziness based particle swarm optimization algorithm

An efficient method is proposed for the design of finite impulse response (FIR) filter with arbitrary pass band edge, stop band edge frequencies and transition width. The proposed FIR band stop filter is designed using craziness based particle swarm optimization (CRPSO) approach. Given the filter specifications to be realized, the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics. In this paper, for the given problem, the realizations of the optimal FIR band pass filters of different orders have been performed. The simulation results have been compared with those obtained by the well accepted evolutionary algorithms, such as Parks and McClellan algorithm (PMA), genetic algorithm (GA) and classical particle swarm optimization (PSO). Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.     

Engineering design optimization based on intelligent response surface methodology

An intelligent response surface methodology （IRSM） was proposed to achieve the most competitive metal forming products, in which artificial intelligence technologies are introduced into the optimization process. It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM, the optimal design space can be reduced greatly without any prior information about function distribution. Also, by identifying the approximation error region, new design points can be supplemented correspondingly to improve the response surface model effectively. The procedure is iterated until the accuracy reaches the desired threshold value. Thus, the global optimization can be performed based on this substitute model. Finally, we present an optimization design example about roll forming of a ＂U＂ channel product.     

基于神经网络的GPS高程拟合方法优选及精度分析

针对现有的几种神经网络GPS高程拟合方法,讨论了利用遗传算法(GA)、粒子群算法(PSO)优化BP神经网络权值和阀值的原理;结合分布较均匀、现势性较好的GPS和水准联测数据,试算了基于神经网络的GPS高程拟合。拟合结果表明:基于PSO算法优化的BP神经网络的拟合精度优于GA算法,误差相对更小。     

基于改进遗传算法的接地网优化设计

为减少接地网均压导体数量和提高均压效果，根据短路时地表电压分布建立了接地网不等间距均压带优化布置的数学模型．优化计算采用改进的遗传算法．介绍了青藏铁路牵引变电所接地网的仿真计算．结果表明，该方法可在满足安全电压的条件下，得到接地网不等间距均压带布置形式．与传统的等间距布置形式相比，可以减少近50％的施工量．     

An Intelligent Response Surface Methodology for Modeling of Domain Level Constraints

An effective modeling method of domain level constraints in the constraint network for concurrent engineering （CE） was developed. The domain level constraints were analyzed and the framework of modeling of domain level constraints based on simulation and approximate technology was given. An intelligent response surface methodology （IRSM） was proposed, in which artificial intelligence technologies are introduced into the optimization process. The design of crank and connecting rod in the V6 engine as example was given to show the validity of the modeling method.     

雷达散射截面实时计算研究的现状与展望

复杂目标雷达散射截面的实时计算是国防科技基础研究中的一个重要问题，在目标的识别与设计、隐身与反隐身等方面有着重要的意义。而以往解决这一问题的方法在计算速度、计算精度等关键因素方面存在着很大的缺陷。本文首先介绍了图形工作站在此领域的应用，并对国内外发展现状作了详尽的分析。然后在此基础上指出了该领域目前存在的关键性问题，重点提出了对应的解决方案。     

悬索桥隧道式锚碇横断面形状对其承载性能影响(英文)

应用有限元软件ABAQUS对比分析了马蹄形和圆形两种横断面隧道式锚碇的承载性能。围岩及锚碇采用实体单元模拟,围岩与锚碇之间设置接触面单元;围岩采用扩展的Mohr-Coulomb屈服模型;使用超载法分析锚碇的极限承载能力。计算结果表明:马蹄形断面在边墙与拱以及边墙与底板的交界处出现较大应力集中,圆形断面应力分布均匀;在断面面积相等的情况下,相同缆力作用下圆形断面锚碇位移小于马蹄形锚碇约22%,极限承载力高出马蹄形锚碇约18%,说明圆形断面承载性能优于马蹄形断面。     

Intelligent optimization of the structure of the large section highway tunnel based on improved immune genetic algorithm

As in the building of deep buried long tunnels, there are complicated conditions such as great deformation, high stress, multi-variables, high non-linearity and so on, the algorithm for structure optimization and its application in tunnel engineering are still in the starting stage. Along with the rapid development of highways across the country, It has become a very urgent task to be tackled to carry out the optimization design of the structure of the section of the tunnel to lessen excavation workload and to reinforce the support. Artificial intelligence demonstrates an extremely strong capability of identifying, expressing and disposing such kind of multiple variables and complicated non- linear relations. In this paper, a comprehensive consideration of the strategy of the selection and updating of the concentration and adaptability of the immune algorithm is made to replace the selection mode in the original genetic algorithm which depends simply on the adaptability value. Such an algorithm has the advantages of both the immune algorithm and the genetic algorithm, thus serving the purpose of not only enhancing the individual adaptability but maintaining the individual diversity as well. By use of the identifying function of the antigen memory, the global search capability of the immune genetic algorithm is raised, thereby avoiding the occurrence of the premature phenomenon. By optimizing the structure of the section of the Huayuan tunnel, the current excavation area and support design are adjusted. A conclusion with applicable value is arrived at. At a higher computational speed and a higher efficiency, the current method is verified to have advantages in the optimization computation of the tunnel project. This also suggests that the application of the immune genetic algorithm has a practical significance to the stability assessment and informationlzation design of the wall rock of the tunnel.     

基于遗传算法的列车端部桁架优化设计

为实现列车端部桁架优化设计,提出了一种将ANSYS和遗传算法有机结合的优化设计方法,该方法是将模型用批处理命令流（APDL）描述,在命令流文件中定义优化目标,设计变量及约束条件,然后遗传算法（GA）把ANSYS的前处理模块作为计算黑箱进行后台调用,从而对吸能结构进行优化设计．以桁架为应用对象,给出了该方法对桁架吸能结构优化设计的全过程,证实把遗传算法引入复杂结构的大规模优化计算是可行的．     

云南山区农村公路设计要点探讨

针对云南省农村公路工程设计中的一些情况,对设计中规范的合理应用,以及农村公路设计中所遇到的平面设计、纵断面设计、横断面设计、排水及路面等问题,结合当地的实际情况提出了解决方案。     

云遗传算法

为了克服传统遗传算法搜索速度慢、易陷入局部最优解的缺陷，借鉴遗传算法的思想，利用云模型云滴的随机性和稳定倾向性的特点，提出了一种新的遗传算法——云遗传算法（CGA）．该算法由正态云模型的Y条件云发生器实现交叉操作，由基本云发生器实现变异操作．最后，进行了函数优化实验，并与标准遗传算法（SGA）和自适应遗传算法（AGA）进行了比较，以证明其有效性．     

A Discrete Bat Algorithm for Disassembly Sequence Planning

Based on the bat algorithm (BA), this paper proposes a discrete BA (DBA) approach to optimize the disassembly sequence planning (DSP) problem, for the purpose of obtaining an optimum disassembly sequence (ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model (FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and differential mutation BA (DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms.     

Forming path optimization for press bending of aluminum alloy aircraft integral panel

Because of the light weight, high stiffness and high structural efficiency, aluminium alloy integral panels are widely used on modern aircrafts. Press bend forming has many advantages, and it becomes a significant technique in aircraft manufacturing field. In order to design the press bend forming path for aircraft integral panels, we propose a novel optimization method which integrates the finite element method (FEM) equivalent model based on our previous study, the artificial neural network response surface, and the genetic algorithm. First, a multi-step press bend forming FEM equivalent model is established, with which the FEM experiments designed with Taguchi method are performed. Then, the back-propagation (BP) neural network response surface is developed with the sample data from the FEM experiments. Further more, genetic algorithm (GA) is applied with the neural network response surface as the objective function. Finally, experimental and simulation verifications are carried out on a single stiffener specimen. The forming error of the panel formed with the optimal path is only 5.37% and the calculating efficiency has been improved by 90.64%. Therefore, this novel optimization method is quite efficient and indispensable for the press bend forming path designing.     

基于分段控制的MMPC排气管段几何建模方法

MMPC系统排气歧管出口形状与入口形状有较大差异。为降低歧管内的流动损失,需要入口形状沿歧管轴线平滑过渡到出口形状,确定歧管截面形状沿歧管轴线的分布规律是实现平滑过渡的前提。给出一种基于分段控制的MMPC排气歧管几何建模方法,建立对出口、入口形状近似程度不同的一组截面,通过各截面在扫描路径上的位置变化,控制MMPC排气歧管段的平滑过渡,为MMPC排气管段的优化设计建立基础。     

Design for Two-degree-of-freedom PID Regulator Based on Improved Generalized Extremal Optimization Algorithm

A kind of new design method for two-degree-of-freedom(2DOF)PID regulator was presented,in which,a new global search heuristic--improved generalized extremal optimization(GEO)algorithm is applied to the parameter optimization design of 2DOF PID regulator.The simulated results show that very good dynamic response performance of both command tracking and disturbance rejection characteristics can be achieved simultaneously.At the same time,the comparisons of simulation results with the improved GA,the basic GEO and the improved GEO were given.From the comparisons,it is shown that the improved GEO algorithm is competitive in performance with the GA and basic GEO and is an attractive tool to be used in the design of two-degree-of-freedom PID regulator.     

张弦梁结构的优化设计方法研究

利用神经网络的强大映射功能,采用拟满应力法分析杆件截面变量的离散性,同时与遗传算法相结合而构成的一种新型组合优化方法．经平面张弦粱结构算例优化分析表明,计算速度快捷、有效可靠且能够满足工程精度要求。     

图形与数据联动的横断面交互设计方法

针对公路路基横断面设计数据量大,断面形式多而复杂的特点,研究了路基横断面自动设计方法。在此基础上,基于对象-属性思想,应用ObjectARX自定义实体技术定制路基横断面实体,并结合反应器与通知技术,开发了基于图形与数据联动的交互设计功能。最后通过实例验证了该交互设计功能的高度自动化和动态可视性。     

Application of conservative surrogate to reliability based vehicle design for crashworthiness

Surrogate models are commonly used for approximation of large computationally expensive vehicle crash simulation to facilitate rapid design space exploration and optimization. Unfortunately, the optimum design based on surrogates may turn out to be infeasible after running finite element crash simulation due to the surrogate errors. To meet this challenge, conservative strategy of surrogate modeling through compensating fitting errors was used for reliability based design optimization of vehicle structures for crashworthiness and weight reduction. The critical crash responses were constructed by unbiased kriging models, and conservative surrogates were obtained via adding safety margin to estimate the crash responses conservatively. The benefits of using conservative surrogates for reliability based design optimization were investigated in the context of constraint feasibility of the optimum designs through a mathematical example and a case study on vehicle crashworthiness design. The results demonstrate that optimization based on conservative surrogate helps to achieve the feasible optimum design, showing more attractive for reliability based design optimization in engineering applications.